We are interested in methods for identifying the genes contributing to complex human diseases, such as hypertension. In our proposed research, we will obtain a detailed characterization of human meiosis, especially with regard to recombinational interference. That work will involve the development of a probability model for human meiosis suitable for use in computer simulations. Using this model, we will study the lengths and persistence of shared chromosomal segments among relatives, and among distantly related individuals in an isolated population. Further, we will develop new, multipoint methods using linkage disequilibrium to identify disease susceptibility genes, and will study the problem of assessing statistical significance in such association studies. Interference can have a great effect on the lengths of shared haplotypes, and so an improved description of interference in human meiosis will be crucial in gaining an understanding of the behavior these shared segments, which may lead to new methods for mapping disease genes. Using disequilibrium to map genes for complex diseases is a very promising approach, but many of the statistical issues regarding these methods are not well understood, especially in genome-wide scans for disequilibrium. Further research will put these methods on more solid footing.